Automatic generation of multipath algorithms in the cellular nonlinear network

The objective of this work is to generate a learning machine capable of find solutions for complex image processing task by Cellular Neural Network (CNN's). First a general machine for automatic analog algorithm design independent of the problem to solve is created, this is accomplished through an evolutionary strategy that is an extension of genetic programming. Second, this work introduces a suite of sub- mechanisms that increase the power of genetic programming and contribute to reduce the enormous space search for producing a plentiful search. Some concepts in this section are related with AI theory, in such a way that in this work we are in the intersection field of AI and Image Processing by CNN.

[1]  Leon O. Chua,et al.  Design of high-speed, high-density CNNS in cmos technology , 1992, Int. J. Circuit Theory Appl..

[2]  R. Caponetto,et al.  Cellular neural network simulator for image processing applications , 1998, 1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359).

[3]  George S. Moschytz,et al.  Stochastic and hybrid approaches toward robust templates , 1998, 1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359).

[4]  P. Szolgay,et al.  An experimental system for optical detection of layout errors of printed circuit boards using learned CNN templates , 1992, CNNA '92 Proceedings Second International Workshop on Cellular Neural Networks and Their Applications.

[5]  Leon O. Chua,et al.  Analogic CNN algorithms for some image compression and restoration tasks , 1995 .

[6]  Leon O. Chua,et al.  The CNN paradigm , 1993 .

[7]  Ángel Rodríguez-Vázquez,et al.  A VLSI-oriented continuous-time CNN model , 1996 .

[8]  Leon O. Chua,et al.  Cellular neural networks: applications , 1988 .

[9]  Lin-Bao Yang,et al.  Cellular neural networks: theory , 1988 .

[10]  J. M. Cruz,et al.  A 16 × 16 Cellular Neural Network Universal Chip: The First Complete Single-Chip Dynamic Computer Array with Distributed Memory and with Gray-Scale Input-Output , 1998 .

[11]  A. Rodriguez-Vazquez,et al.  A 64/spl times/64 CNN universal chip with analog and digital I/O , 1998, 1998 IEEE International Conference on Electronics, Circuits and Systems. Surfing the Waves of Science and Technology (Cat. No.98EX196).

[12]  Krzysztof Salot.  Cellular neural network design for solving specific image-processing problems , 1992, Int. J. Circuit Theory Appl..

[13]  Tamás Szirányi,et al.  Texture Classification and Segmentation by Cellular Neural Networks Using Genetic Learning , 1998, Comput. Vis. Image Underst..